Research map / Probabilistic and scientific modeling / Molecules and proteins
DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use DeepPseudo instead of the strongest baseline | Competing-risk analysis · SEER | time-dependent C-index: 0.876 -> 0.877; 0.808 -> 0.813; 0.846 -> 0.852; 0.803 -> 0.814 | Helped |
| Use DeepPseudo instead of the strongest baseline | Competing-risk analysis · WIHS | time-dependent C-index: 0.734 -> 0.734; 0.646 -> 0.654; 0.691 -> 0.702; 0.676 -> 0.684 | Mixed |
| Use DeepPseudo instead of the strongest baseline | Competing-risk analysis · Synthetic | time-dependent C-index: 0.753 -> 0.761; 0.682 -> 0.703; 0.752 -> 0.760; 0.679 -> 0.699 | Helped |
| Use about 50k parameters rather than about 1M parameters | M-DP on SEER · SEER | C-index | Mixed |
| Use modified pseudo values for covariate-dependent censoring | DeepPseudo · CRA experiments | C-index | No clear effect |
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